Author Correction: Closed-loop brain training: the science of neurofeedback

Sitaram, Ranganatha; Ros, Tomas; Stoeckel, Luke E.; Haller, Sven; Scharnowski, Frank; Lewis-Peacock, Jarrod A.; Weiskopf, Nikolaus; Blefari, Maria Laura; Rana, Mohit; Oblak, Ethan; Birbaumer, Niels; Sulzer, James

doi:10.1038/s41583-019-0161-1

Cited by 4 publications

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“…Further, by characterizing the spectral dynamics involved in this process, our data may also provide important information to guide neuromodulation techniques aiming to measure and/or regulate attentional states with enhanced resistance to distractors (Romei et al 2010;Sitaram et al 2019;Bagherzadeh et al 2020). In sum, we show that spectral activity of the human amygdala during prestimulus time intervals may have direct or indirect functional impact on subsequent face visual awareness, particularly during conditions with degraded inputs.…”

Section: Discussionmentioning

confidence: 99%

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Prestimulus amygdala spectral activity is associated with visual face awareness

et al. 2022

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Alpha cortical oscillations have been proposed to suppress sensory processing in the visual, auditory, and tactile domains, influencing conscious stimulus perception. However, it is unknown whether oscillatory neural activity in the amygdala, a subcortical structure involved in salience detection, has a similar impact on stimulus awareness. Recording intracranial electroencephalography (EEG) from 9 human amygdalae during face detection in a continuous flash suppression task, we found increased spectral prestimulus power and phase coherence, with most consistent effects in the alpha band, when faces were undetected relative to detected, similarly as previously observed in cortex with this task using scalp-EEG. Moreover, selective decreases in the alpha and gamma bands preceded face detection, with individual prestimulus alpha power correlating negatively with detection rate in patients. These findings reveal for the first time that prestimulus subcortical oscillations localized in human amygdala may contribute to perceptual gating mechanisms governing subsequent face detection and offer promising insights on the role of this structure in visual awareness.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Prestimulus amygdala spectral activity is associated with visual face awareness

et al. 2022

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“…Three parts, that is, humans (input devices), machines (output devices), and communications constitute HMI systems, achieving the processes of giving feedback to humans and instructing the machines. [ 44,128,129 ] After capturing the human‐perceivable signals, the data processing and communication processes between humans and machines are crucial to give commands to electrical readouts (output devices). [ 130,131 ] For example, Figure a presents a simple robot control HMI system based on a tactile sensor.…”

Section: Principle and Design Strategy Of Communication And Output Dementioning

confidence: 99%

Wearable Sensors‐Enabled Human–Machine Interaction Systems: From Design to Application

Yin

Wang

Zhao

et al. 2020

Adv Funct Materials

480

227

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In comparison to traditional bulky and rigid electronic devices, the human–machine interaction (HMI) system with flexible and wearable components is an inevitable future trend. To achieve effective, intuitive, and seamless manipulation of high‐performance wearable HMI systems, it is important to develop effective strategies for designing material microstructures on flexible sensors and electric devices with excellent mechanical flexibility and stretchability. The real‐time acquisition of human physiology and surrounding signals through accurate and flexible sensors is the basis of wearable HMIs. Herein, the construction of a wearable HMI system that utilizes sensors, communication modes, and actuators is reviewed. The mechanisms and strategies for designing various flexible sensors based on different mechanisms are analyzed and discussed. The functional mechanism, material selection, and novel design strategies of each part are summarized in detail. The different communication modes in interactive systems and the manufacturing technology of soft machines are also introduced. Additionally, the most advanced applications of wearable HMI systems in intelligent identification and security, interactive controls for robots, augmented reality, and virtual reality have been highlighted. The review concludes with an overview of the remaining key challenges and several ideas regarding the further improvement of wearable HMI systems.

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“…Neurofeedback is a form of biofeedback that allows individuals to control their brain function by measuring neural activity and presenting this information in real-time (Ehlis et al, 2018 ; Sitaram et al, 2019 ). The method is typically used to record brain waves and provide feedback (Marzbani et al, 2016 ), and near-infrared spectroscopy (NIRS) devices are new tools for neurofeedback training (Ehlis et al, 2018 ).…”

Section: Introductionmentioning

confidence: 99%

Construction and evaluation of a neurofeedback system using finger tapping and near-infrared spectroscopy

Takahashi,

Kuroiwa

et al. 2024

Front. Neuroimaging

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IntroductionNeurofeedback using near-infrared spectroscopy (NIRS) has been used in patients with stroke and other patients, but few studies have included older people or patients with cognitive impairment.MethodsWe constructed a NIRS-based neurofeedback system and used finger tapping to investigate whether neurofeedback can be implemented in older adults while finger tapping and whether brain activity improves in older adults and healthy participants. Our simple neurofeedback system was constructed using a portable wearable optical topography (WOT-HS) device. Brain activity was evaluated in 10 older and 31 healthy young individuals by measuring oxygenated hemoglobin concentration during finger tapping and neurofeedback implementation.ResultsDuring neurofeedback, the concentration of oxygenated hemoglobin increased in the prefrontal regions in both the young and older participants.DiscussionThe results of this study demonstrate the usefulness of neurofeedback using simple NIRS devices for older adults and its potential to mitigate cognitive decline.

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Author Correction: Closed-loop brain training: the science of neurofeedback

Abstract: An acknowledgement to Mohit Rana's funding source was also missing. The following sentence should have been included in the acknowledgments section: M.R. is supported by a Fondecyt postdoctoral fellowship (project no. 3100648).

Cited by 4 publications

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Prestimulus amygdala spectral activity is associated with visual face awareness

Prestimulus amygdala spectral activity is associated with visual face awareness

Wearable Sensors‐Enabled Human–Machine Interaction Systems: From Design to Application

Construction and evaluation of a neurofeedback system using finger tapping and near-infrared spectroscopy

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